[WIP] Upload folder using huggingface_hub (multi-commit 6cf6053f290e75261f02574e3d94b5c617f08fc504a85116a6d65848081ed0a5)

#6
README.md CHANGED
@@ -1,5 +1,6 @@
1
  ---
2
  thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
 
3
  metrics:
4
  - memory_disk
5
  - memory_inference
@@ -30,7 +31,7 @@ tags:
30
  - Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
31
  - Request access to easily compress your *own* AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
32
  - Read the documentations to know more [here](https://pruna-ai-pruna.readthedocs-hosted.com/en/latest/)
33
- - Join Pruna AI community on Discord [here](https://discord.gg/rskEr4BZJx) to share feedback/suggestions or get help.
34
 
35
  ## Results
36
 
@@ -39,7 +40,7 @@ tags:
39
  **Frequently Asked Questions**
40
  - ***How does the compression work?*** The model is compressed with llm-int8.
41
  - ***How does the model quality change?*** The quality of the model output might vary compared to the base model.
42
- - ***How is the model efficiency evaluated?*** These results were obtained on NVIDIA A100-PCIE-40GB with configuration described in `model/smash_config.json` and are obtained after a hardware warmup. The smashed model is directly compared to the original base model. Efficiency results may vary in other settings (e.g. other hardware, image size, batch size, ...). We recommend to directly run them in the use-case conditions to know if the smashed model can benefit you.
43
  - ***What is the model format?*** We use safetensors.
44
  - ***What calibration data has been used?*** If needed by the compression method, we used WikiText as the calibration data.
45
  - ***What is the naming convention for Pruna Huggingface models?*** We take the original model name and append "turbo", "tiny", or "green" if the smashed model has a measured inference speed, inference memory, or inference energy consumption which is less than 90% of the original base model.
@@ -59,15 +60,15 @@ You can run the smashed model with these steps:
59
  2. Load & run the model.
60
  ```python
61
  from transformers import AutoModelForCausalLM, AutoTokenizer
 
62
 
63
- model = AutoModelForCausalLM.from_pretrained("PrunaAI/facebook-opt-125m-bnb-8bit-smashed",
64
- trust_remote_code=True, device_map='auto')
65
- tokenizer = AutoTokenizer.from_pretrained("facebook/opt-125m")
66
 
67
- input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
68
 
69
- outputs = model.generate(input_ids, max_new_tokens=216)
70
- tokenizer.decode(outputs[0])
71
  ```
72
 
73
  ## Configurations
 
1
  ---
2
  thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
3
+ base_model: facebook/opt-125m
4
  metrics:
5
  - memory_disk
6
  - memory_inference
 
31
  - Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
32
  - Request access to easily compress your *own* AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
33
  - Read the documentations to know more [here](https://pruna-ai-pruna.readthedocs-hosted.com/en/latest/)
34
+ - Join Pruna AI community on Discord [here](https://discord.gg/CP4VSgck) to share feedback/suggestions or get help.
35
 
36
  ## Results
37
 
 
40
  **Frequently Asked Questions**
41
  - ***How does the compression work?*** The model is compressed with llm-int8.
42
  - ***How does the model quality change?*** The quality of the model output might vary compared to the base model.
43
+ - ***How is the model efficiency evaluated?*** These results were obtained on HARDWARE_NAME with configuration described in `model/smash_config.json` and are obtained after a hardware warmup. The smashed model is directly compared to the original base model. Efficiency results may vary in other settings (e.g. other hardware, image size, batch size, ...). We recommend to directly run them in the use-case conditions to know if the smashed model can benefit you.
44
  - ***What is the model format?*** We use safetensors.
45
  - ***What calibration data has been used?*** If needed by the compression method, we used WikiText as the calibration data.
46
  - ***What is the naming convention for Pruna Huggingface models?*** We take the original model name and append "turbo", "tiny", or "green" if the smashed model has a measured inference speed, inference memory, or inference energy consumption which is less than 90% of the original base model.
 
60
  2. Load & run the model.
61
  ```python
62
  from transformers import AutoModelForCausalLM, AutoTokenizer
63
+
64
 
65
+ model = AutoModelForCausalLM.from_pretrained("PrunaAI/facebook-opt-125m-bnb-8bit-smashed", trust_remote_code=True, device_map='auto')
66
+ tokenizer = AutoTokenizer.from_pretrained("facebook/opt-125m")
 
67
 
68
+ input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
69
 
70
+ outputs = model.generate(input_ids, max_new_tokens=216)
71
+ tokenizer.decode(outputs[0])
72
  ```
73
 
74
  ## Configurations
config.json CHANGED
@@ -1,5 +1,5 @@
1
  {
2
- "_name_or_path": "/tmp/tmp5b6mpxn_",
3
  "_remove_final_layer_norm": false,
4
  "activation_dropout": 0.0,
5
  "activation_function": "relu",
@@ -24,7 +24,10 @@
24
  "pad_token_id": 1,
25
  "prefix": "</s>",
26
  "quantization_config": {
 
 
27
  "bnb_4bit_compute_dtype": "bfloat16",
 
28
  "bnb_4bit_quant_type": "fp4",
29
  "bnb_4bit_use_double_quant": false,
30
  "llm_int8_enable_fp32_cpu_offload": false,
@@ -38,7 +41,7 @@
38
  "quant_method": "bitsandbytes"
39
  },
40
  "torch_dtype": "float16",
41
- "transformers_version": "4.37.1",
42
  "use_cache": true,
43
  "vocab_size": 50272,
44
  "word_embed_proj_dim": 768
 
1
  {
2
+ "_name_or_path": "/efs/sommer/cache/wdzixvjngwsxmo90",
3
  "_remove_final_layer_norm": false,
4
  "activation_dropout": 0.0,
5
  "activation_function": "relu",
 
24
  "pad_token_id": 1,
25
  "prefix": "</s>",
26
  "quantization_config": {
27
+ "_load_in_4bit": false,
28
+ "_load_in_8bit": true,
29
  "bnb_4bit_compute_dtype": "bfloat16",
30
+ "bnb_4bit_quant_storage": "uint8",
31
  "bnb_4bit_quant_type": "fp4",
32
  "bnb_4bit_use_double_quant": false,
33
  "llm_int8_enable_fp32_cpu_offload": false,
 
41
  "quant_method": "bitsandbytes"
42
  },
43
  "torch_dtype": "float16",
44
+ "transformers_version": "4.44.2",
45
  "use_cache": true,
46
  "vocab_size": 50272,
47
  "word_embed_proj_dim": 768
generation_config.json CHANGED
@@ -3,5 +3,5 @@
3
  "bos_token_id": 2,
4
  "eos_token_id": 2,
5
  "pad_token_id": 1,
6
- "transformers_version": "4.37.1"
7
  }
 
3
  "bos_token_id": 2,
4
  "eos_token_id": 2,
5
  "pad_token_id": 1,
6
+ "transformers_version": "4.44.2"
7
  }
merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:47e0d1186b99bc2ddb6998a65a74abe24a91369167c3162e01e39a1323d7d645
3
- size 165905184
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1a094a9afa29b8d44e9362c18d980db67fbcf80061c194d6ae598c298e68e685
3
+ size 165913552
smash_config.json CHANGED
@@ -8,14 +8,25 @@
8
  "compilers": "None",
9
  "task": "text_text_generation",
10
  "device": "cuda",
11
- "cache_dir": "/ceph/hdd/staff/charpent/.cache/modelsl3ypgxtn",
12
  "batch_size": 1,
13
- "tokenizer": "GPT2TokenizerFast(name_or_path='facebook/opt-125m', vocab_size=50265, model_max_length=1000000000000000019884624838656, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'bos_token': '</s>', 'eos_token': '</s>', 'unk_token': '</s>', 'pad_token': '<pad>'}, clean_up_tokenization_spaces=True), added_tokens_decoder={\n\t1: AddedToken(\"<pad>\", rstrip=False, lstrip=False, single_word=False, normalized=True, special=True),\n\t2: AddedToken(\"</s>\", rstrip=False, lstrip=False, single_word=False, normalized=True, special=True),\n}",
14
- "model_config": "{'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'float16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': True, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['OPTForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': '</s>', 'bos_token_id': 2, 'pad_token_id': 1, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'facebook/opt-125m', 'transformers_version': '4.37.1', 'activation_dropout': 0.0, 'model_type': 'opt', 'vocab_size': 50272, 'max_position_embeddings': 2048, 'num_attention_heads': 12, 'word_embed_proj_dim': 768, 'ffn_dim': 3072, 'hidden_size': 768, 'num_hidden_layers': 12, 'dropout': 0.1, 'attention_dropout': 0.0, 'activation_function': 'relu', 'init_std': 0.02, 'layerdrop': 0.0, 'use_cache': True, 'do_layer_norm_before': True, 'enable_bias': True, 'layer_norm_elementwise_affine': True, '_remove_final_layer_norm': False}",
15
- "model_name": "facebook/opt-125m",
 
 
 
 
 
 
 
 
 
16
  "pruning_ratio": 0.0,
17
- "n_quantization_bits": 8,
18
- "output_deviation": 0.005,
 
 
19
  "max_batch_size": 1,
20
  "qtype_weight": "torch.qint8",
21
  "qtype_activation": "torch.quint8",
 
8
  "compilers": "None",
9
  "task": "text_text_generation",
10
  "device": "cuda",
11
+ "cache_dir": "/efs/sommer/cache/wdzixvjn",
12
  "batch_size": 1,
13
+ "tokenizer_name": "GPT2TokenizerFast(name_or_path='facebook/opt-125m', vocab_size=50265, model_max_length=1000000000000000019884624838656, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'bos_token': '</s>', 'eos_token': '</s>', 'unk_token': '</s>', 'pad_token': '<pad>'}, clean_up_tokenization_spaces=True), added_tokens_decoder={\n\t1: AddedToken(\"<pad>\", rstrip=False, lstrip=False, single_word=False, normalized=True, special=True),\n\t2: AddedToken(\"</s>\", rstrip=False, lstrip=False, single_word=False, normalized=True, special=True),\n}",
14
+ "pruning_type": "structured-taylor",
15
+ "sparsity_level": 0.5,
16
+ "head_pruning_ratio": 0.5,
17
+ "iterative_steps": 1,
18
+ "sequence_length": 2048,
19
+ "calibration_data_size": 10,
20
+ "global_pruning": false,
21
+ "ignore_embeddings": false,
22
+ "prune_head_dims": false,
23
+ "prune_num_heads": true,
24
+ "ignored_layers": "[0, 1, 10, 11]",
25
  "pruning_ratio": 0.0,
26
+ "model_configs": "{'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'float16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': True, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['OPTForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': '</s>', 'bos_token_id': 2, 'pad_token_id': 1, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'facebook/opt-125m', 'transformers_version': '4.44.2', 'activation_dropout': 0.0, 'model_type': 'opt', 'vocab_size': 50272, 'max_position_embeddings': 2048, 'num_attention_heads': 12, 'word_embed_proj_dim': 768, 'ffn_dim': 3072, 'hidden_size': 768, 'num_hidden_layers': 12, 'dropout': 0.1, 'attention_dropout': 0.0, 'activation_function': 'relu', 'init_std': 0.02, 'layerdrop': 0.0, 'use_cache': True, 'do_layer_norm_before': True, 'enable_bias': True, 'layer_norm_elementwise_affine': True, '_remove_final_layer_norm': False}",
27
+ "model_name": "facebook/opt-125m",
28
+ "weight_quantization_bits": 8,
29
+ "output_deviation": 0.0,
30
  "max_batch_size": 1,
31
  "qtype_weight": "torch.qint8",
32
  "qtype_activation": "torch.quint8",
special_tokens_map.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "</s>",
4
+ "lstrip": false,
5
+ "normalized": true,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "</s>",
11
+ "lstrip": false,
12
+ "normalized": true,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": {
17
+ "content": "<pad>",
18
+ "lstrip": false,
19
+ "normalized": true,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "unk_token": {
24
+ "content": "</s>",
25
+ "lstrip": false,
26
+ "normalized": true,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ }
30
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "1": {
6
+ "content": "<pad>",
7
+ "lstrip": false,
8
+ "normalized": true,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "2": {
14
+ "content": "</s>",
15
+ "lstrip": false,
16
+ "normalized": true,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ }
21
+ },
22
+ "bos_token": "</s>",
23
+ "clean_up_tokenization_spaces": true,
24
+ "eos_token": "</s>",
25
+ "errors": "replace",
26
+ "legacy": false,
27
+ "model_max_length": 1000000000000000019884624838656,
28
+ "pad_token": "<pad>",
29
+ "tokenizer_class": "GPT2Tokenizer",
30
+ "unk_token": "</s>"
31
+ }
vocab.json ADDED
The diff for this file is too large to render. See raw diff